A comparison of modelling techniques for computing wall stress in abdominal aortic aneurysms.

Doyle BJ, Callanan A, McGloughlin TM - Biomed Eng Online (2007)

Bottom Line:
It was also noted that wall stress was shown to reduce by 59% when modelled using the most accurate non-linear complex approach, compared to the same model without intraluminal thrombus.The results here show that using more realistic parameters affect resulting wall stress.Care should be taken when examining stress results found using simplified techniques, in particular, if the wall stress results are to have clinical importance.

Affiliation: Centre for Applied Biomedical Engineering Research (CABER), Department of Mechanical and Aeronautical Engineering and Materials and Surface Science Institute, University of Limerick, Ireland. barry.doyle@ul.ie

ABSTRACT

Background: Aneurysms, in particular abdominal aortic aneurysms (AAA), form a significant portion of cardiovascular related deaths. There is much debate as to the most suitable tool for rupture prediction and interventional surgery of AAAs, and currently maximum diameter is used clinically as the determining factor for surgical intervention. Stress analysis techniques, such as finite element analysis (FEA) to compute the wall stress in patient-specific AAAs, have been regarded by some authors to be more clinically important than the use of a "one-size-fits-all" maximum diameter criterion, since some small AAAs have been shown to have higher wall stress than larger AAAs and have been known to rupture.

Methods: A patient-specific AAA was selected from our AAA database and 3D reconstruction was performed. The AAA was then modelled in this study using three different approaches, namely, AAA(SIMP), AAA(MOD) and AAA(COMP), with each model examined using linear and non-linear material properties. All models were analysed using the finite element method for wall stress distributions.

Results: Wall stress results show marked differences in peak wall stress results between the three methods. Peak wall stress was shown to reduce when more realistic parameters were utilised. It was also noted that wall stress was shown to reduce by 59% when modelled using the most accurate non-linear complex approach, compared to the same model without intraluminal thrombus.

Conclusion: The results here show that using more realistic parameters affect resulting wall stress. The use of simplified computational modelling methods can lead to inaccurate stress distributions. Care should be taken when examining stress results found using simplified techniques, in particular, if the wall stress results are to have clinical importance.

Figure 5: von Mises wall stress distributions for both the AAA(SIMP)L and AAA(SIMP)NL models at an internal pressure of 120 mmHg. Wall stress results are normalised to the peak stress found AAA(SIMP)L. The black mark indicates the region of peak wall stress. Models are shown in the anterior view.

Mentions:
In order to easily observe and visualise the resulting wall stress of each AAA model, contours of the von Mises stress were plotted on the surface of each AAA model. The von Mises stress is a stress index especially suited for failure analysis, as stress is a tensor quantity with nine components, with the von Mises stress being a combination of these components [7]. The normalised computed wall stress results for the AAA(SIMP), AAA(MOD) and AAA(COMP) models can be seen in Figures 5, 6 and 7. In these figures, wall stress results were normalised by using the peak stress experienced in the linearly elastic model of each case. In each case, the linearly elastic model returned a higher peak stress than the corresponding non-linear model. The location of peak stress remained the same in all models except the AAA(SIMP) models, where the location of peak stress shifted from a centred anterior location to a left lateral location. For both linearly elastic and non-linearly elastic AAA(MOD) and AAA(COMP) models, the peak stress region was located on the inner surface of the AAA wall. When using 3D stress elements the stress is not interpolated through the wall thickness, as with shell elements, but rather at the individual integration points of the element. For the AAA(COMP) models the peak stress was located at regions between the intersection of the ILT region and the AAA wall.

Figure 5: von Mises wall stress distributions for both the AAA(SIMP)L and AAA(SIMP)NL models at an internal pressure of 120 mmHg. Wall stress results are normalised to the peak stress found AAA(SIMP)L. The black mark indicates the region of peak wall stress. Models are shown in the anterior view.

Mentions:
In order to easily observe and visualise the resulting wall stress of each AAA model, contours of the von Mises stress were plotted on the surface of each AAA model. The von Mises stress is a stress index especially suited for failure analysis, as stress is a tensor quantity with nine components, with the von Mises stress being a combination of these components [7]. The normalised computed wall stress results for the AAA(SIMP), AAA(MOD) and AAA(COMP) models can be seen in Figures 5, 6 and 7. In these figures, wall stress results were normalised by using the peak stress experienced in the linearly elastic model of each case. In each case, the linearly elastic model returned a higher peak stress than the corresponding non-linear model. The location of peak stress remained the same in all models except the AAA(SIMP) models, where the location of peak stress shifted from a centred anterior location to a left lateral location. For both linearly elastic and non-linearly elastic AAA(MOD) and AAA(COMP) models, the peak stress region was located on the inner surface of the AAA wall. When using 3D stress elements the stress is not interpolated through the wall thickness, as with shell elements, but rather at the individual integration points of the element. For the AAA(COMP) models the peak stress was located at regions between the intersection of the ILT region and the AAA wall.

Bottom Line:
It was also noted that wall stress was shown to reduce by 59% when modelled using the most accurate non-linear complex approach, compared to the same model without intraluminal thrombus.The results here show that using more realistic parameters affect resulting wall stress.Care should be taken when examining stress results found using simplified techniques, in particular, if the wall stress results are to have clinical importance.

Affiliation:
Centre for Applied Biomedical Engineering Research (CABER), Department of Mechanical and Aeronautical Engineering and Materials and Surface Science Institute, University of Limerick, Ireland. barry.doyle@ul.ie

ABSTRACT

Background: Aneurysms, in particular abdominal aortic aneurysms (AAA), form a significant portion of cardiovascular related deaths. There is much debate as to the most suitable tool for rupture prediction and interventional surgery of AAAs, and currently maximum diameter is used clinically as the determining factor for surgical intervention. Stress analysis techniques, such as finite element analysis (FEA) to compute the wall stress in patient-specific AAAs, have been regarded by some authors to be more clinically important than the use of a "one-size-fits-all" maximum diameter criterion, since some small AAAs have been shown to have higher wall stress than larger AAAs and have been known to rupture.

Methods: A patient-specific AAA was selected from our AAA database and 3D reconstruction was performed. The AAA was then modelled in this study using three different approaches, namely, AAA(SIMP), AAA(MOD) and AAA(COMP), with each model examined using linear and non-linear material properties. All models were analysed using the finite element method for wall stress distributions.

Results: Wall stress results show marked differences in peak wall stress results between the three methods. Peak wall stress was shown to reduce when more realistic parameters were utilised. It was also noted that wall stress was shown to reduce by 59% when modelled using the most accurate non-linear complex approach, compared to the same model without intraluminal thrombus.

Conclusion: The results here show that using more realistic parameters affect resulting wall stress. The use of simplified computational modelling methods can lead to inaccurate stress distributions. Care should be taken when examining stress results found using simplified techniques, in particular, if the wall stress results are to have clinical importance.